• Relevant Coursework: Tech Product Management, Design Thinking, Customer Analytics• Member: Kellogg Tech Club, Kellogg Data and Analytics Club• Capstone Project: Optimizing product assortment with machine learning for Fortune 500 retailer

I led a team of UX researchers and marketing professionals to identify target personas for a paid subscription product, refine the unique value proposition for each audience, and design a personalized digital experience for each persona. In collaboration with engineers and data scientists, I then designed machine learning tests (set to launch in Q4 2022) to assess the effectiveness of these efforts. Specific accomplishments include:• Designed roadmap for personalized customer experience to grow overall paid member revenue through increased customer acquisition• Led team of data scientists, UX researchers, and engineers to identify customer friction points and design three machine learning tests to improve online customer experience

I led a team of engineers, UX researchers, and business specialists to launch a data visualization software product to help department heads manage costs, assess talent gaps, and ensure diversity in their organizations. I also oversaw all reporting and analytics related to the largest corporate restructuring in firm history. Specific accomplishments include:• Directed firmwide voluntary early retirement initiative aiming to reduce workforce costs and revamp firm’s technical knowledge base• Devised and implemented machine learning models to predict attrition of workforce in key technical roles, allowing for more strategic deployment of contractors • Enabled an increase in female leadership representation by building more robust descriptive analytics capabilities to create transparency into firm’s workforce• Managed cross-functional team of three in designing and implementing new data visualization software used to assess impact of a major workforce initiative

I helped leading companies in the technology, financial services, and manufacturing industries to a) identify markets where they could cost-effectively hire talent with the requisite skills, b) conduct competitive intelligence on what other employers operated in those markets, and c) refine their value proposition so they could differentiate themselves to potential employees. I also applied statistical modeling to enable clients to ensure they maintained pay equity in their organizations. Specific accomplishments include:• Developed data analysis and reporting tool that predicted healthcare workforce shortages within each US state, laying basis for project sales to hospitals and healthcare clinics• Revamped project management processes and programming codebase for workforce planning projects for technology clients, automating future workflows to cut project turnaround time• Spearheaded cross-functional project identifying and evaluating emerging technology workforce hotspots for client, allowing client to reduce forecasted costs• Created new applications for machine learning methods for predicting pay equity outcomes, improving model accuracy to better identify and reduce pay disparities within technology client’s organization

I worked to expand our marketing footprint, personalize our messaging for key clients, implement A/B tests to assess the effectiveness of that messaging, and identify marketing qualified leads to pass on to the sales team. I also partnered with the sales team to use marketing-generated insights to refine their sales pitches to key clients. Specific accomplishments include:• Overhauled marketing and sales analytics processes to enable better identification of potential clients and allow for more targeted upsell messaging, driving an increase in event sponsorship sales• Oversaw internship program managing ten people per quarter to ensure talent pipeline across departments